Induction of Mean Output Prediction Trees from Continuous Temporal Meteorological Data
Journal Title: Journal of Applied Quantitative Methods - Year 2009, Vol 4, Issue 4
Abstract
In this paper, we present a novel method for fast data-driven construction of regression trees from temporal datasets including continuous data streams. The proposed Mean Output Prediction Tree (MOPT) algorithm transforms continuous temporal data into two statistical moments according to a user-specified time resolution and builds a regression tree for estimating the prediction interval of the output (dependent) variable. Results on two benchmark data sets show that the MOPT algorithm produces more accurate and easily interpretable prediction models than other state-of-the-art regression tree methods.
Authors and Affiliations
Dima ALBERG, Mark LAST, Avner BEN-YAIR
Keywords
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